Search Results - EGA European Genome-Phenome Archive

Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

Study EGAS00001005403

Test Study for EGA using data from 1000 Genomes Project - Phase 3

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

Study EGAS00001005042

NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

Study phs003047

RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

Dataset EGAD50000000333

RNA-Seq in Patients with Primordial Dwarfism

Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001000640

Small cell number RNA-seq (400 cells per sample)

Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

Dataset EGAD50000001830

Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

Dataset EGAD00001009496

CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study

This is a case-control study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This sample has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3 (See Porjesz et al., 2005; Porjesz and Rangaswamy, 2007 for reviews). A brief description of COGA is in Edenberg, H. J. (2002) The Collaborative Study on the Genetics of Alcoholism: an update. Alcohol Res Health 26, 214-218., Bierut, LJ, NL Saccone, JP Rice, A Goate, T Foroud, HJ Edenberg, L Almasy, PM Conneally, R Crowe, V Hesselbrock, T-K Li, JI Nurnberger, Jr, B Porjesz, MA Schuckit, J Tischfield, H Begleiter, and T Reich (2002) Defining alcohol-related phenotypes in humans: The Collaborative Study on the Genetics of Alcoholism. Alcohol Res Health 26, 208-213. Edenberg HJ and Foroud T (2006) The genetics of alcoholism: identifying specific genes through family studies. Addiction Biology 11, 386-396. This case-control sample of biologically unrelated individuals was drawn from COGA subjects. All cases meet DSM-IV criteria for alcohol dependence. Controls are individuals who have consumed alcohol, but did not meet any definition of alcohol dependence or alcohol abuse, nor did they meet any DSM-IIIR or DSM-IV definition of abuse or dependence for other drugs (except nicotine). All cases and controls have undergone identical clinical assessments. Many individuals in this case-control sample have not previously been genotyped. The Collaborative Study on the Genetics of Alcoholism (COGA) has four Co-Principal Investigators: B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-Investigators are: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, A. Goate, J. Rice); University of California at San Diego (M. Schuckit); Howard University (R. Taylor); Rutgers University (J. Tischfield); Southwest Foundation (L. Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438),and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). COGA has over 250 publications listed at www.niaaagenetics.org

Study phs000125

Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma

Primary central nervous system (CNS) gliomas can be classified by characteristic genetic alterations. In addition to solid tissue obtained by surgery or biopsy, cell-free DNA (cfDNA) derived from cerebrospinal fluid (CSF) is an alternative source of material for genomic analyses. Experimental design: We performed targeted next-generation sequencing (NGS) of CSF cfDNA in a representative cohort of 85 patients presenting with with suspicion of primary or recurrent glioma at two neurooncological centers. Copy-number variation (CNV) profiles, single nucleotide variants (SNVs), and small insertions/ deletions (indels) were combined into a molecular-guided tumor classification. Comparison with the solid tumor was performed for 38 cases with matching solid tissue available. Results: Cases were stratified into four groups: glioblastoma (n = 32), other glioma (n = 19), non-malignant (n = 17) and no confirmed diagnosis available (n = 17). We introduce a molecular-guided tumor classification, enabling identification of tumor entities and/ or cancer specific alterations in 75.0 % (n = 24) of glioblastoma and 52.6 % (n = 10) of other glioma cases. The overlap between CSF and matching solid tissue was highest for CNVs (26-48 %) and SNVs at pre-defined gene loci (44 %), followed by SNVs/indels identified via uninformed variant calling (8-14 %). A molecular-guided tumor classification was made 23.5 % (n = 4) of cases with no confirmed diagnosis available. Conclusions: We developed a workflow for targeted sequencing of CSF cfDNA as well as a strategy for interpretation and reporting of sequencing results based on a molecular-guided tumor classification in glioma.

Study EGAS50000000060

Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

Identifying causative genes via genetic testing is useful for the screening, prevention, and treatment of cancer. Several hereditary syndromes are known to occur in renal cell carcinoma (RCC). However, these evidences came from the European population; it remains unclear how the RCC-related genes and other cancer-predisposing genes contribute to the development RCC in the Japanese population. A case-control study of 14 RCC-related genes and 26 cancer-predisposing genes was performed using 1,563 Japanese patients with RCC and 6,016 controls. Patients were divided into two major histological subtypes of clear cell RCC (ccRCC) or non-clear cell RCC (nccRCC). Gene-based analysis of germline pathogenic variants in patients with each subtype and cancer-free subjects was performed. Following quality control, 1,532 patients with RCC and 5,996 controls were further analyzed. For ccRCC, 52 of 1,283 (4.05%) patients carried pathogenic variants mainly in the cancer-predisposing genes such as TP53 (P = 1.73 �� 10-4; OR, 5.8; 95% CI, 2.2��15.7). Approximately 80% of patients with pathogenic variants in TP53 had p.Ala189Val that was specific in East Asian population. For nccRCC, 14 of 249 (5.62%) patients carried pathogenic variants mainly in the RCC-related genes such as BAP1 (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0��Inf), and FH (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0��Inf). Our study showed different and population-specific contributions of risk genes between ccRCC and nccRCC in Japanese for better-personalized medicine.

Study JGAS000414

Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

Background: Patients with glioblastoma without MGMT promoter hypermethylation are unlikely to benefit from temozolomide (TMZ). Trials aiming at replacing TMZ with targeted agents in not molecularly selected patient populations have failed. Methods: This phase I/IIa umbrella trial aimed at showing safety, feasibility, and preliminary efficacy of targeted compounds in addition to standard radiotherapy initiated within 42 days postoperatively. Molecular diagnostics and bioinformatic evaluation are performed within 28 days after surgery. Stratification for treatment takes place in five subtrials, including alectinib, idasanutlin, palbociclib, vismogedib and temsirolimus, according to the best matching molecular alteration. Patients without matching alterations are randomized between subtrials without strong biomarkers using atezolizumab and asunercept and TMZ as standard of care. Primary objective of the phase I parts of the trial was dose finding or dose validation. In the phase IIa trials, centrally determined progression-free survival at six months (PFS-6) is used as endpoint for efficacy with interim analyses for futility (H0: p=0.231). Results: From May 2018 through July 2022, 301 patients were enrolled and 228 treated in 13 German NOA sites. The alectinib and vismodegib subtrials were closed since no molecularly matching patients were accrued; the idasanutlin subtrial was closed prior to the optimal dose at nine patients at discretion of the company providing the drug. The TMZ subtrial showed a PFS-6 of 18.52% (10/54 patients) (p=0.831) and a median overall survival (OS) of 12.1 months. Asunercept: PFS-6 of 15.4% (4/26) (p=0.8825) and OS of 12.8 months. Atezolizumab: PFS-6 of 21.4% (9/42) (p=0.660) and OS of 11.7 months. Palbociclib with patients demonstrating CDK4 amplification or CDKN2A/B codeletion: PFS-6 of 24.4% (10/41) (p=0.4823) and OS of 12.6 months. Temsirolimus with patients demonstrating mTOR activation: PFS-6 of 39.1% (18/46) (p=0.0109) and OS of 15.4 months. The regimen-limiting toxicity (RLT)-rate is 34.8%, which is insignificantly above the predefined unacceptable rate for RLTs of 30%. Most RLTs had severity grade 3, one RLT had severity grade 4. No RLTs resulted in death. Conclusions: N2M2 allows for elaborate molecular testing being integrated into the treatment decision and efficient determination of treatment activity for patients with newly diagnosed glioblastoma. There is clinical activity of temsirolimus in patients with tumors harboring an activated mTOR pathway although this is not positively prognostic without mTOR inhibition; there is no clinical activity for asunercept and atezolizumab in not molecularly selected patients and also palbociclib in molecularly selected patients.

Study EGAS00001008033

Single-cell RNA-seq of human kidney tumors

Fresh nephrectomy samples were collected from a total of 5 untreated ccRCC patients. Out of these 5 patients, 7 samples were obtained. Two samples consisted of fresh versus frozen single cells from the primary tumor site of one patient. Two other samples consisted of matched primary and distant thrombus sites (the vena cava) of a second patient. The three remaining samples came from the primary tumor sites of three distinct ccRCC patients. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry. Sequencing was performed on a Illumina HiSeq 4000 sequencer.

Dataset EGAD00001009306

Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

This study is multi-omics study of a Asian longitudinal metastatic breast cancer (MBC) cohort treated with palbociclib plus endocrine therapy. It contains NGS of baseline (BL) and progressive disease (PD) from 70 patients, consisting of 79 tumor/normal matched whole exome sequencing (WES) from 62 patients and 90 tumor whole transcriptome sequecing samples (WTS) from 70 patients. There were 56 BL biopsies profiled by WES and 64 by WTS; 23 PD biopsies were profiled by WES and 26 by WTS. Twenty and 23 patients had paired BL and PD biopsies profiled by WES and WTS, respectively.

Dataset EGAD00001008314

Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

Study phs000892

Latency and interval therapy affect the evolution in metastatic colorectal cancer

While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g. those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of dormancy in the evolutionary path of metastatic CRC.

Study EGAS00001003646

Dataset for NSCLC-RNA

Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008846

Dataset for liposarcoma-RNA

Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008854

Epigenetic Profiling of Human Colorectal Cancer

DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

Study phs000385

CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

Study phs000930

Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

Study EGAS00001002499

BRCA1 secondary splice-site mutations

BRCA1 splice isoforms d11 and d11q can contribute to PARP inhibitor (PARPi) resistance by splicing-out mutation-containing exons, producing truncated, partially-functional proteins. However, the clinical impact and underlying drivers of BRCA1 exon skipping remain undetermined. We analyzed nine ovarian and breast cancer patient derived xenografts (PDX) with BRCA1 exon 11 frameshift mutations for splice isoform expression and therapy response.

Study EGAS50000000022

Luminal progenitor cell line iHBEC(CD117)

Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

Dataset EGAD50000000723

NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (Ischemic Stroke Genetic Study, ISGS)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Ischemic Stroke Genetics Study (ISGS) is a study of newly onset cases (~600) with ischemic stroke (a stroke due to sudden interruption of blood flow to a part of the brain) compared with sex- and age-matched non-stroke participants. The study was conducted to determine the genes and their variants that contribute to an individual's risk of developing an ischemic stroke. The coordination of the recruitment and flow of the samples occurred at the Mayo Clinic, Jacksonville, FL, under the direction of James F. Meschia, MD. The University of Virginia (Stephen S. Rich, PhD) served as the analytic site for the genetic data. All GWAS data on ISGS participants have been deposited into dbGaP. As part of the NHLBI Exome Sequencing Project, DNA from a subset of ISGS participants will undergo exome sequencing. For the NHLBI ESP, a subset of 92 individuals with lacunar (small vessel) or atherosclerotic (large vessel) TOAST subtypes were selected from among all ISGS participants, excluding those individuals with TOAST subtypes of stroke of other etiology or of stroke with undetermined etiology. All 92 samples pass initial quality control metrics and 89 samples completed exome sequencing. A total of 75 participants with appropriate consent and variant calls had their genetic and phenotypic data deposited into dbGaP.

Study phs000546

Transcriptomic Analysis of Human Hematopoietic Progenitors from Healthy Donors and Bone Marrow Failure Patients

The purpose of this study was to define transcriptional changes that occur in the rare and heterogeneous bone marrow progenitors that are affected in Shwachman-Diamond Syndrome. Data are reported for four genetically confirmed SDS patients ranging from 11-26 years old, 3 male and 1 female, and four healthy donors ranging from 25-29 years old, 2 male and 2 female. Subjects provided written, informed consent in accordance with the Declaration of Helsinki's Ethical Principles of Medical Research Involving Human Subjects. Single CD34+ cells were purified from fresh bone marrow and cDNA libraries were prepared using the SMARTer Ultra Low RNA Kit (Clontech; pre-2015) or SMART-Seq v4 Ultra Low RNA Kit (Clontech; post-2015). Libraries were sequenced on a HiSeq 2500 Instrument (Illumina, San Diego, CA) to a read depth of ~3 M paired-end, 25 bp reads per single cell. Paired-end reads were mapped to the hg38 human transcriptome (Gencode v24) using STAR v2.4.2a.

Study phs001845

Integrative Age-Related Changes in Genome and Epigenome in Human Lung in Relation to Smoking

The Integrative Age-Related Changes in Genome and Epigenome in Human Lung in Relation to Smoking study was designed to assess DNA methylation and gene expression profiles in cytologically normal bronchial progenitor "basal" cells. The cells were collected from 54 consented bronchoscopy specimen donors at standard airway locations during clinically indicated bronchoscopy, and then outgrown in primary cultures. DNA methylation profiles were assessed using Enzymatic-Methyl sequencing (EM-seq: 96% genomic coverage, 7.5x depth) in all 54 donors' samples. The gene expression profile was evaluated by bulk RNA-Seq in 39 donors' samples. The study participants were at the ages of 33 - 81 years old at enrollment. Of the 54 donors, 31 were newly diagnosed with lung cancer. As for tobacco smoke exposure, there were 19 current, 18, former, and 17 never smokers. There are 26 subjects whose specimens were used for single cell whole-genome sequencing study phs002758.

Study phs003317

Feasibility and safety of a multi-cancer blood test for screening and intervention

We evaluated the feasibility and safety of blood testing for cancer in an interventional study of 10,006 women. Positive tests for DNA or protein were independently confirmed and diagnostic PET-CT imaging was used to localize disease. During the study, 26 cancers were first detected by blood testing, 24 more by standard-of-care screening, and 46 by neither approach. Surgicalexcision of the primary tumors was performed on 12 cancers first detected by blood testing.1.0% of participants underwent PET-CT imaging based on false positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multi-cancer blood testing, when followed by PET-CT localization, can be safely incorporated into routineclinical care, in some cases leading to surgery with intent to cure. Further studies will be required to determine the clinical validity and utility of multi-cancer blood testing.

Study EGAS00001004372

Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

Dataset EGAD00001010876

Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren’s pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Participants underwent extensive medical assessment for Sjögren's Syndrome using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's syndrome, the Genomic Summary Results from this GWAS are being made available herein using a total of n=3232 Sjögren's cases and n=17,481 controls. A total of n=8962 controls were obtained from our SGENE collaborators or from our previous study (Lessard, et al. Nature Genetics 2013. PMID: 24097067). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were also obtained from dbGaP (phs000428.v2.p2; phs000672.v1.p1; phs000196.v3.p1; phs000187.v1.p1). In accordance with IRB approval, subject consents, and data sharing restrictions, we are also making available the individual-level genotyping data for a subset of Sjögren's cases (n=1,199) that were genotyped at the OMRF.

Study phs002723

Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

Study EGAS00001000135

IMCISION DNAseq

Standard-of-care (SOC) surgery for locoregionally advanced head and neck squamous cell carcinoma (HNSCC) is intensive and results in 30‒50% five-year overall survival. Anti-PD1 immune checkpoint blockade (ICB) durably improves survival rates in recurrent/metastatic HNSCC. We report on the non-randomized phase Ib/IIa IMCISION trial (NCT03003637) of 32 HNSCC patients treated with two doses neoadjuvant nivolumab (NIVO MONO, n=6, phase Ib arm A) or two doses of nivolumab plus a single dose of ipilimumab (COMBO, n=26, 6 in phase Ib arm B and 20 in phase IIa) prior to surgery and, if indicated, adjuvant radiotherapy. Neoadjuvant ICB was feasible in all phase Ib patients, meeting the phase Ib primary feasibility endpoint. One phase IIa patient had progressive disease precluding surgery. Primary tumor pathological response (phase IIa primary endpoint), defined as the % change in viable tumor cells from baseline biopsy to on-treatment resection, was evaluable in 29 patients. . We observed a major pathological response (MPR, 90‒100% response) in 8/23 (35%) evaluable COMBO and 1/6 (17%) NIVO MONO patients. None of the patients with MPR after NIVO MONO or COMBO developed a tumor relapse after 24.0 months median follow-up. FDG-PET-based total lesion glycolysis identified MPR patients prior to surgery. A baseline AID/APOBEC-associated mutational profile and an on-treatment decrease in hypoxia signature expression were observed in MPR patients. Our data indicate that neoadjuvant NIVO MONO and COMBO are safe in HNSCC, and that particularly COMBO ICB shows encouraging effectivity. IMCISION provides rationales for future HNSCC trials aiming to pre-operatively select patients with a likely MPR after neoadjuvant ICB for de-escalation of SOC.

Study EGAS00001005466

OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

Study EGAS00001004832

OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

Study EGAS00001004833

10x Genomics raw data of intestinal plasma cells

The dataset contains raw fastq files (fastq.gz) for Chromium Single Cell 5’ gene expression (GEX), human B cell VDJ and feature barcode (CSP) sequencing from transglutaminase 2-specific and other small intestinal plasma cells isolated from four untreated celiac disease patients. Single cell 5’ gene expression, V(D)J-enriched and cell surface protein libraries were generated using Chromium single cell kits, and barcoded cDNA from a total of 5,000-10,000 cells per sample was generated using the 10x Genomics Chromium Controller. The libraries were pooled prior to sequencing on a NovaSeq 6000 instrument (Illumina) using the following configuration: read 1: 26 cycles, read 2: 89 cycles, index read 1: 8 cycles.

Dataset EGAD50000000342

Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

Dataset EGAD50000001557

ICR96 exon CNV validation series

A resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect.

Dataset EGAD00001003335

Prevention and Early Treatment of Acute Lung Injury Network - Vitamin D to Improve Outcomes by Leveraging Early Treatment (PETAL VIOLET-BioLINCC)

Data Access NOTE: Please refer to the "Authorized Access" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL VIOLET include Plasma and Whole Blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Specimens may not be used to produce commercial products.Objectives: To evaluate the effect of short-term vitamin D supplementation on mortality among critically ill patients with a vitamin D deficiency.Background: Observational data indicate that vitamin D deficiency is common among critically ill patients and constitutes a potentially modifiable risk factor associated with longer lengths of stay in the hospital and intensive care unit (ICU), lung and other organ injury, prolonged mechanical ventilation, and death. In a previous phase 2 trial, vitamin D supplementation administered to vitamin D-deficient, critically ill patients was associated with lower observed mortality than placebo at 28 days and at 6 months. Because of the need for a larger, phase 3 trial, the PETAL-VIOLET study was initiated to determine if early administration of high-dose vitamin D3 would reduce all-cause mortality among critically ill patients with a vitamin D deficiency.Participants: 1360 patients underwent randomization, 690 were assigned to the vitamin D group and 668 were assigned to the placebo group. Of the 1078 patients confirmed to have a vitamin D deficiency by liquid chromatography-tandem mass spectrometry (LC-MS-MS), 538 had been assigned to the vitamin D group and 540 had been assigned to the placebo group.Design: PETAL-VIOLET was a multicenter, double-blind, placebo-controlled, phase 3 trial. Patients were enrolled within 12 hours after the clinician's decision to admit the patient to the ICU from the emergency department, hospital ward, operating room, or outside facility. Patients were tested for vitamin D deficiency, with a threshold of plasma 25-hydroxyvitamin D level of less than 20 ng per milliliter. Patients were randomly assigned in a 1:1 ratio, stratified according to site, to receive either a single enteral (administered orally or through a nasogastric or orogastric tube) dose of 540,000 IU of vitamin D3 or matched placebo, in liquid form, administered within 2 hours after randomization.Conclusions: After the first interim analysis, the data and safety monitoring board recommended that the trial be stopped for futility.A single 540,000 IU enteral dose of vitamin D3 administered early during critical illness rapidly corrected vitamin D deficiency but did not provide an advantage over placebo with respect to mortality or other clinically important end points.

Study phs003879

Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

Therapeutic interventions modulating immune function at the tumor site could improve outcomes in cancer. Here we analyzed metastatic melanoma, a tumor type highly responsive to T-cell based therapies, and found that the tumor-infiltrating T cells are localized closely to CD14+ monocytes/macrophages rather than to melanoma cells. Using novel immunofluorescence-guided laser capture micro-dissection, we analyzed transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages and melanoma cells in non-dissociated tissue. CD14+ cells localized in tumors beds displayed specific transcriptional signatures distinct from CD14+ cells that were localized in tumor stroma.The 8 distinct metastatic melanoma samples are from the Cooperative Human Tissue Network (CHTN). 64 RNA-seq files are available from 16 intraCD14+, 16 stromaCD14+, 16 cancer cells, 8 intraCD3+ and 8 stromaCD3+ cells. 2 LCM harvests were completed for the CD14+ and cancer cells on two sections of the samples. One harvest was done for the CD3+ samples.The processed data (TPM/raw counts tables) are available on GEO under GSE180124. 

Study phs002564

Genomic Profiling of Sequentially Acquired Metastatic Sites from an "Exceptional Responder" Lung Adenocarcinoma Patient Reveals Extensive Genomic Heterogeneity and Novel Somatic Variants

We employed next-generation sequencing to identify somatic alterations in multiple metastatic sites from an "exceptional responder" lung adenocarcinoma patient during his seven year course of ERBB2-directed therapies. The degree of heterogeneity was unprecedented, with ~1% similarity between somatic alterations of the lung and lymph nodes. One novel translocation, PLAG1-ACTA2, present in both sites, up-regulated ACTA2 expression. ERBB2, the predominant driver oncogene, was amplified in both sites, more pronounced in the lung, and harbored an L869R mutation in the lymph node. Functional studies demonstrated increased proliferation, migration, metastasis, and resistance to ERBB2-directed therapy due to L869R mutation and increased migration due to ACTA2 overexpression. Within the lung, a nonfunctional CDK12, due to a novel G879V mutation, correlated with down-regulation of DNA damage response genes, causing genomic instability, and sensitivity to chemotherapy. We propose a model whereby a sub-clone metastasized early from the primary site and evolved independently in lymph nodes.

Study phs001159

WES in HCCOs with varying Doxorubicin resistance

We aimed to identify somatic mutations that could explain the resistance to Doxorubicin. Therefor, we purified Exomes from liver biopsies and HCC organoids using Agilent SureSelectXT (clinical research exome, HS2 V8, or Human all Exon V6 Cosmic) and performed WES. Matched non-tumoral liver biopsies served as the control for germline mutations. 12 of these samples were previously reported. Sequence reads were aligned to the reference human genome GRCh38 using Burrows-Wheeler Aligner (BWA, v0.7.17). Duplicate removal, base quality adjustment, mutation calling (Mutect2, intervals: SureSelectXT_HS_V8_S33266340, germline-recourse: gnomad.exomes.r2.1.1.sites.liftover_grch38, Panel-of-Normal: 1000g_pon.hg38), filtering of Mutect calls, and functional annotation (Funcotator, funcotator_dataSources.v1.7.20200521g) were performed using the Genome Analysis Toolkit (GATK, v4.4) according to the Broad Institute best practices in Somatic short variant discovery workflows. Mutations with a functional annotation of Deletion, Insertion, Non-stop, Splice-Site, Start-Codon and Missense mutations were kept. A list of 43 commonly mutated genes in HCC was analyzed in the HCC organoids [TCGA, Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell, 2017. 169(7): p. 1327-1341.e23].

Study EGAS50000000043

Epigenetic and metabolomic data from type 2 diabetes adolescents

Objective: Rates of type 2 diabetes (T2D) among adolescents are on the rise. Epigenetic changes could be associated with the metabolic alterations in adolescents with T2D. Methods: We performed a cross-sectional integrated analysis of DNA methylation data from peripheral blood mononuclear cells with serum metabolomic data from First Nation adolescents with T2D and controls participating in the Improving Renal Complications in Adolescents with type 2 diabetes through REsearch (iCARE) cohort study, to explore the molecular changes in adolescents with T2D. Results: Our analysis showed that 43 serum metabolites and 36 differentially methylated regions (DMR) were associated with T2D. Several DMRs were located near the transcriptional start site of genes with established roles in metabolic disease and associated with altered serum metabolites (e.g. glucose, leucine, and gamma-glutamylisoleucine). These included the free fatty acid receptor-1 (FFAR1), upstream transcription factor-2 (USF2), and tumor necrosis factor-related protein-9 (C1QTNF9), among others. Conclusions: We identified DMRs and metabolites that merit further investigation to determine their significance in controlling gene expression and metabolism which could define T2D risk in adolescents.

Study EGAS00001003816

An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

We describe the creation and characterization of an isogenic cell line panel representing common cancer pathways, with multiple features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cells were generated using CRISPR-technologies. Surprisingly, we discovered most of these lines did not result in complete gene inactivation, despite integration of sgRNA at the desired genomic site. However, a subset of the lines harbored true, biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterize lines covering 19 pathways frequently subject to loss of function in cancers. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a multiplexed high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena

Study EGAS00001005974

CCDG CVD: VIRGO - Variation in Recover-Role of Gender on Outcomes of Young Acute Myocardial Infarction (AMI) Patients

The VIRGO study is a four year research project funded by the NHLBI to study young women and men with heart attacks. A total of 2,000 women who are 18 - 55 years of age and a smaller comparison group of 1,000 similarly aged men will be enrolled in this multi-site observational study from approximately 120 different hospitals across the country. Young women have a much greater risk of dying after an acute myocardial infarction (AMI) than similarly aged men. Their mortality risk is markedly higher than that of young men, and limited data on young minority women suggest that they may have the highest risk of any young subgroup. Findings from the small number of published studies of young women with ischemic heart disease suggest that the biology, epidemiology, care, and outcomes of this group are distinct from those of men. To date, there have been no large studies of this population, even as the death toll is comparable to that from breast cancer in this country. This study will help researchers identify key factors that influence recovery from a heart attack and potentially improve the care and outcomes of young women and men with AMI. Specific Aims: To investigate the excess risk in young women with AMI and to identify key demographic, clinical, metabolic, psychosocial, health care delivery, and biological determinants of prognosis, we propose a national, prospective, observational study of 2,000 women who are 55 years or younger with AMI and a smaller comparison group of 1,000 men. Our prior work and preliminary studies indicate that the sex differences are most prominent in this age group and suggest that by 1 year after discharge, there are substantial sex differences in outcomes. We will also develop risk stratification tools that will help clinicians to identify young women with the highest and lowest risk. Specific Aim 1: Determine sex differences in outcomes following AMI. Specific Aim 2: Determine sex differences in the prevalence and prognostic importance of demographic, clinical, and psychosocial risk factors. Specific Aim 3:Determine sex differences in quality of care. Specific Aim 4: Determine sex differences in the prevalence and prognostic importance of selected biochemical biomarkers following AMI. These samples have been whole genome sequenced as part of the NHGRI's Center for Common Disease Genetics at the Broad Institute.

Study phs001259

Heart Failure Network Oral Iron Repletion Effects on Oxygen Uptake in Heart Failure (HFN IRONOUT-BioLINCC)

ObjectivesTo test the hypothesis that, compared to placebo, oral iron repletion in heart failure patients with iron deficiency improves exercise capacity after 16 weeks of therapy.Background Iron deficiency affects approximately one half of patients with symptomatic heart failure. The presence of iron deficiency in patients with heart failure is associated with reduced functional capacity, poorer quality of life, and increased mortality. Despite growing recognition of the significance of iron deficiency, randomized multicenter trials exploring the utility of oral iron supplementation, a therapy that is inexpensive, readily available, and safe, have not been performed in patients with heart failure. Moreover, patient characteristics and biochemical profiles that may influence responsiveness to oral iron in patients with heart failure have not been defined. Results of intravenous iron repletion trials have been favorable, but regularly treating patients with intravenous iron products is expensive and poses logistical challenges for outpatients. Therefore, the HFN-IRONOUT study was initiated to investigate the efficacy of oral iron in patients with heart failure with reduced ejection fraction (HFrEF). ParticipantsA total of 225 participants were enrolled, 111 randomized to receive oral iron and 114 randomized to receive the placebo. Design The HFN-IRONOUT study was a phase 2, double-blind, placebo-controlled randomized clinical trial that enrolled participants at 23 sites in the United States. Participants were randomly assigned, in a 1:1 ratio, to receive either oral iron polysaccharide or placebo with the use of an automated web-based system. A permuted block randomization method (with 4 participants per block) was stratified by enrolling site and anemia status (defined as hemoglobin At baseline, 8 weeks, and 16 weeks participants underwent studies including history and physical examination, cardiopulmonary exercise testing (CPET), Kansas City Cardiomyopathy Questionnaire (KCCQ), and 6-minute walk test. CPETs were performed using a 10 Watt/minute incremental ramp protocol and breath-by-breath measures of oxygen uptake were uniformly analyzed by the CPET Core Lab. Participants also underwent phlebotomy for biomarkers. Iron studies, including iron, total iron binding capacity, and ferritin, were measured at baseline and after 16 weeks to determine the extent to which oral iron led to iron repletion. The primary end point was the change in peak oxygen uptake (peak VO2) after 16 weeks of therapy. Conclusions Among participants with HFrEF with iron deficiency, high-dose oral iron did not improve exercise capacity over 16 weeks.

Study phs003557

Single cell RNAseq FASTQ files of three PDAC organoid lines (P28, P40, P47) using SORT-seq

This dataset contains raw FASTQ files from single cell RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47) cultured under standard conditions. For each line, single cells were FACS sorted into 384-well capture plates, with each well containing a 50nl droplet of barcoded primers. Plates were processed following an adapted SORT-seq protocol, and cDNA libraries were generated using CEL-Seq2 with TruSeq small RNA primers (Illumina). Sequencing was performed on an Illumina NextSeq500 platform using paired-end reads (read 1: 26 cycles, index read: 6 cycles, read 2: 60 cycles). Data are controlled-access and intended for single cell transcriptomic analysis of PDAC organoid heterogeneity and WNT pathway activity.

Dataset EGAD50000002220

San Francisco Bay Area Latina Breast Cancer Study

The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

Study phs000912

Losartan Effects on Emphysema Progression (LEEP-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To evaluate the efficacy of losartan, an angiotensin receptor blocker, to reduce emphysema progression in patients with COPD and mild to moderate emphysema. Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease comprising chronic bronchitis and emphysema. COPD is a major cause of morbidity and mortality. Smoking cessation slows the progression of the disease, and bronchodilators can provide sustained improvement in lung function, but there are no pharmacologic agents that clearly modify emphysema progression. Angiotensin receptor blockers (ARBs) have been suggested as potential drugs to slow the progression of COPD. A few trials have shown that patients treated with ARBs had slower progression of radiographic emphysema. The LEEP study was initiated to test the hypothesis that the ARB losartan would reduce the progression of emphysema in patients with COPD with mild to moderate emphysema.ParticipantsA total of 220 participants were enrolled. 108 participants were randomized to receive losartan, and 112 participants were randomized to receive the placebo.Design LEEP was a randomized, placebo-controlled multicenter trial. Participants were randomly assigned (1:1) to receive losartan or placebo. The dose was 50 mg losartan or placebo given as one capsule daily for 2 weeks, and, if well tolerated and the systolic blood pressure was >90 mm Hg, it was increased to two capsules. Participants and site investigators were masked to treatment assignment. Participant responses to the St George's Respiratory Questionnaire, the modified Medical Research Council dyspnea scale, the COPD Assessment Test, and the Physical Function–Short Form 20a were collected. The number and severity of COPD exacerbations were recorded. COPD exacerbations were defined as two or more new or worse symptoms for ≥3 days and classified by treatment as mild (neither antibiotics nor oral steroids), moderate (an antibiotic or oral steroid), or severe (hospitalization). The primary outcome measure was the change in quantitative whole-lung emphysema score after 48 weeks measured by the percentage of lung voxels less than -950 Hounsfield units (PCT950) on full inspiratory HRCT. Conclusions Losartan does not prevent progression of emphysema in patients with COPD who have mild to moderate pulmonary emphysema.

Study phs004313

Whole Exome Sequencing of Congenital Diaphragmatic Hernia Patients and Trios

Congenital diaphragmatic hernia (CDH) is a common and severe birth defect characterized by structural defects of the diaphragm and by pulmonary hypoplasia. Congenital diaphragmatic hernia patient may present either as an isolated phenotype or together with other congenital anomalies in a complex phenotype. Despite the clinical significance of CDH, the underlying genetic and developmental pathways are incompletely understood. In order to establish a catalog of human genetic variation for this condition, we performed whole exome sequencing (WES) on 275 carefully phenotyped individuals with CDH in the Pediatric Surgical Research Laboratories at the Massachusetts General Hospital (Boston, MA, USA) and Boston Children's Hospital (Boston, MA, USA). The exome data generated are valuable for comparison of candidate genes derived from WES of other CDH cohorts or affected kindreds, and to provide ideal candidates for further functional studies with the ultimate goal of enhancing our understanding of the heterogeneous and, possibly, oligogenic molecular etiology of CDH. While familial clustering has been reported in rare kindreds, the majority of probands with CDH have no family history of CDH leading to the hypothesis that de novo variants are an important and relatively frequent etiological mechanism. In the second version of the study, we performed WES analysis on 87 trios, to assess the contribution of de novo mutations in the etiology of diaphragmatic and pulmonary defects and to identify previously unknown candidate genes. This dbGaP submission includes WES data on: (a) 20 new probands, (b) 9 probands also reported in the previous version (dbGaP accession no. phs000783.v1.p1), (c) 174 unaffected parents, including the parents of 67 previously reported probands. Combined analysis with other available cohorts of congenital diaphragmatic hernia revealed a genome-wide enrichment of likely gene-disrupting de novo variants (i.e., nonsense, frameshift or splice site), and missense de novo variants predicted in silico to be damaging.

Study phs000783

IMCISION DNAseq

Whole-exome sequencing of 32 primary head and neck squamous cell carcinoma samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy. DNA quantity used: 50ng. Library Preparation Kit: Twist Human Core Exome Plus (Twist Bioscience). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ.

Dataset EGAD00001008139

FEGA and European GDI: working together to improve human health

The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

Blog fega-and-gdi

PyEGA3 download client

PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

Documentation access/download/files/pyega3

6168 results for "mmoga fc coins Buyfc26coins.com is FC 26 coins official site..dH5e"

in 24.19 milliseconds.

Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

Test Study for EGA using data from 1000 Genomes Project - Phase 3

NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

RNA-Seq in Patients with Primordial Dwarfism

Small cell number RNA-seq (400 cells per sample)

Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study

Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma

Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

Single-cell RNA-seq of human kidney tumors

Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

Latency and interval therapy affect the evolution in metastatic colorectal cancer

Dataset for NSCLC-RNA

Dataset for liposarcoma-RNA

Epigenetic Profiling of Human Colorectal Cancer

CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

BRCA1 secondary splice-site mutations

Luminal progenitor cell line iHBEC(CD117)

NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (Ischemic Stroke Genetic Study, ISGS)

Transcriptomic Analysis of Human Hematopoietic Progenitors from Healthy Donors and Bone Marrow Failure Patients

Integrative Age-Related Changes in Genome and Epigenome in Human Lung in Relation to Smoking

Feasibility and safety of a multi-cancer blood test for screening and intervention

Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

IMCISION DNAseq

OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

10x Genomics raw data of intestinal plasma cells

Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

ICR96 exon CNV validation series

Prevention and Early Treatment of Acute Lung Injury Network - Vitamin D to Improve Outcomes by Leveraging Early Treatment (PETAL VIOLET-BioLINCC)

Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

Genomic Profiling of Sequentially Acquired Metastatic Sites from an "Exceptional Responder" Lung Adenocarcinoma Patient Reveals Extensive Genomic Heterogeneity and Novel Somatic Variants

WES in HCCOs with varying Doxorubicin resistance

Epigenetic and metabolomic data from type 2 diabetes adolescents

An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

CCDG CVD: VIRGO - Variation in Recover-Role of Gender on Outcomes of Young Acute Myocardial Infarction (AMI) Patients

Heart Failure Network Oral Iron Repletion Effects on Oxygen Uptake in Heart Failure (HFN IRONOUT-BioLINCC)

Single cell RNAseq FASTQ files of three PDAC organoid lines (P28, P40, P47) using SORT-seq

San Francisco Bay Area Latina Breast Cancer Study

Losartan Effects on Emphysema Progression (LEEP-BioLINCC)

Whole Exome Sequencing of Congenital Diaphragmatic Hernia Patients and Trios

IMCISION DNAseq

FEGA and European GDI: working together to improve human health

PyEGA3 download client